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研究生:邱泓彰
研究生(外文):Hong-Chang Chiou
論文名稱:基於模糊類神經控制器之多變數控制系統設計
論文名稱(外文):Multivariable Process Control Using Decentralized Neural Fuzzy Controllers
指導教授:陳奇中陳奇中引用關係
指導教授(外文):Chyi-Tsong Chen
學位類別:碩士
校院名稱:逢甲大學
系所名稱:化學工程學系
學門:工程學門
學類:化學工程學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
論文頁數:85
中文關鍵詞:多變數系統模糊類神經控制器智能控制
外文關鍵詞:Multivariable systemNeural fuzzy controllerIntelligent process control
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隨著控制對象越來越趨向於複雜以及希望同時達到控制多個輸出的前提下,使用智能控制是目前可以實現的方式之一;也因為如此,本文提供在智能控制裡一種新的控制策略,利用模糊類神經控制器來控制多變數系統。使用模糊類神經控制器的好處是其可以隨著控制目標的不同,透由參數修正方法,自行調整控制器的輸出以達到控制性能的實現。另外由於多變數系統本身存在著大小不一的交互作用問題以及控制輸入跟控制輸出間的配對常因系統的模式而有所不同,所以本文基於以上兩個問題,分別以加入靜態解偶器及迴路間配對法則來加以克服。接著我們將利用模糊類神經控制器及所建構之多變數系統控制架構分別測試化工上經常使用到之蒸餾塔系統及固體燃料燃燒系統上。最後從系統回應圖上,可以顯示出模糊類神經控制器本身的優越性能,並證明了針對多變數系統,使用模糊類神經控制器是一個可行的方向。
This dissertation develops an intelligent control system for multivariable process systems using decentralized neural fuzzy controllers. With an incorporated static decoupler, the neural fuzzy controllers are able to learn to control the multivariable process adaptively by adjusting their membership functions as well as the fuzzy rules. The intelligent control scheme and the related parameter tuning rules derived based on steepest descent algorithm are presented systematically. To show the effectiveness of the intelligent control system, the simulation applications in this work include this control of Wood and Berry distillation column, solid-fuel system and a nonlinear distillation process. Extensive simulation results reveal that the proposed decentralized neural/fuzzy control system appears to be a promising approach to the intelligent control of multivariable process systems, which can provide satisfactory control performance and shorten the design time.
目錄
中文摘要…………………………………………………………………I
英文摘要………………………………………………………………..Ⅱ
目錄…………………………………………………………………….…i
圖目錄…………………………………………………………………...iv
表目錄…………………………………………………………………...vi
符號說明………………………………………………………………..vii
第一章 緒論……………………………………………………….……1
1-1 前言…………………………………………………………….….1
1-2 多變數系統控制之難題……………………………….………….2
1-3 多變數控制系統控制架構與策略…………………….………….4
1-4 研究動機……………………………………………….………….6
1-5 論文組織……………………………………………….………….7
第二章 模糊類神經控制系統……………………………….………..9
2-1 前言……………………………………………………….……….9
2-2 傳統模糊控制系統……………………………………….……….9
2-2.1 模糊概述……………………………………………………….10
2-2.2 模糊控制系統架構…………………………………………….11
2-2.3 多變數模糊控制器常面臨之問題…………………….………12
2-3 類神經控制系統…………………………………………..…..13
2-3.1 類神經網路概述……………………………………………..13
2-3.2 類神經網路結構……………………………………………..14
2-3.3 類神經網路之運作…………………………………………..15
2-3.4 類神經網路學習方法………………………………………..16
2-3.5 類神經網路在模糊邏輯上之應用…………………………..17
2-4 模糊類神經控制系統…………………………………………..18
2-4.1 模糊類神經控制系統設計…………………………………..22
2-4.2 模糊類神經控制器參數學習法……………………………..24
2-5 模糊類神經控制器於單變數系統之控制..…………………..26
2-6 結論……………………………………………………………..27
第三章 基於模糊類神經控制器之多變數系統…………………….28
3-1 前言……………………………………………………………..28
3-2 多變數系統簡介………………………………………………..29
3-3 迴路間的配對與去偶化………………………………………..30
3-3.1 迴路間的配對方法…………………………………………..30
3-3.2 系統之去偶化…………………………………………………33
3-4 控制系統架構…………………………………………………..35
3-5 結論……………………………………………………………..36
第四章 多變數控制系統於化工上之應用…………………………..37
4-1 前言……………………………………………………………….37
4-2 燃煤多變數系統……………….………………………………..38
4-3 Wood and Berry 蒸餾塔系統……………………………………39
4-4 基於非線性模式之蒸餾塔系統控制模擬….….……………...43
4-5 結論……………………………………………………………...46
第五章 結論與未來展望……………………………………………..48
5-1 結論……………………………………………………………...48
5-2 未來展望…………………………………………………….…..49
參考文獻………………………………………………………….…..69
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